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Understanding statistical significance.

BACKGROUND: Statistical significance is often misinterpreted as proof or scientific evidence of importance. This article addresses the most common statistical reporting error in the biomedical literature, namely, confusing statistical significance with clinical importance. OBJECTIVE: The aim of this...

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Published in:Nursing Research Vol. 59; no. 3; pp. 219 - 224
Main Author: Hayat MJ
Format: tables/charts Journal Article
Published: Lippincott Williams & Wilkins May/Jun2010
Online Access:View this record in EBSCOhost
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      dt: May/Jun2010
      vid: 59
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      pub: Lippincott Williams & Wilkins
      place: Baltimore, Maryland
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        atl: Understanding statistical significance.
      aug:
        au: Hayat MJ
        affil: School of Nursing, Johns Hopkins University, Baltimore, Maryland 21205, USA. mhayat2@son.jhmi.edu
      sug:
        subj:
          Data Analysis, Statistical
          Statistical Significance
          Confidence Intervals
          Effect Size
          Null Hypothesis
          Sample Size
      ab: BACKGROUND: Statistical significance is often misinterpreted as proof or scientific evidence of importance. This article addresses the most common statistical reporting error in the biomedical literature, namely, confusing statistical significance with clinical importance. OBJECTIVE: The aim of this study was to clarify the confusion between statistical significance and clinical importance by providing a historical perspective of significance testing, presenting a correct understanding of the information given by p values and significance testing, and offering recommendations for the correct use and reporting of statistical results. APPROACH: The correct interpretation of p values and statistical significance is given, and the recommendations provided include a description of the current recommended guidelines for statistical reporting of the size of an effect. RESULTS: This article provides a comprehensive overview of p values and significance testing and an understanding of the need for measures of importance and magnitude in statistical reporting. DISCUSSION: Statistical significance is not an objective measure and does not provide an escape from the requirement for the researcher to think carefully and judge the clinical and practical importance of a study's results.
      pubtype: Academic Journal
      doctype:
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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